Alibabaie et al., 2019 - Google Patents
Fuzzy Notch Filter for Periodic and Quasi-Periodic Noise Reduction in Digital ImagesAlibabaie et al., 2019
View PDF- Document ID
- 3758358080333191474
- Author
- Alibabaie N
- Latif A
- Publication year
- Publication venue
- Journal of Machine Vision and Image Processing
External Links
Snippet
Periodic noises damage the visual quality of images by imposing repetitive patterns on them. In the Fourier amplitude spectrum, they appear as spike-like components. In this research work, we introduce a new method that is based on fuzzy systems for de-noising …
- 230000000737 periodic 0 title abstract description 10
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20172—Image enhancement details
- G06T2207/20182—Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
- G06T2207/20064—Wavelet transform [DWT]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
- G06T2207/20056—Discrete and fast Fourier transform, [DFT, FFT]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
- G06T5/001—Image restoration
- G06T5/002—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20016—Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
- G06T5/001—Image restoration
- G06T5/003—Deblurring; Sharpening
- G06T5/004—Unsharp masking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
- G06T5/20—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image by the use of local operators
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
- G06T5/007—Dynamic range modification
- G06T5/008—Local, e.g. shadow enhancement
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Harikiran et al. | Impulse noise removal in digital images | |
CN111179186A (en) | Image denoising system for protecting image details | |
Sur | An a-contrario approach to quasi-periodic noise removal | |
Fawwaz et al. | The edge detection enhancement on satellite image using bilateral filter | |
Alibabaie et al. | Fuzzy Notch Filter for Periodic and Quasi-Periodic Noise Reduction in Digital Images | |
Nadernejad et al. | PDEs-based method for image enhancement | |
Kumar et al. | Image enhancement and performance evaluation using various filters for IRS-P6 Satellite Liss IV remotely sensed data | |
Papari et al. | Contour detection by multiresolution surround inhibition | |
Kaur et al. | Image de-noising techniques: a review paper | |
Moallemi et al. | Adaptive optimum notch filter for periodic noise reduction in digital images | |
Butt et al. | Multilateral filtering: A novel framework for generic similarity-based image denoising | |
Tavassoli et al. | A new method for impulse noise reduction from digital images based on adaptive neuro-fuzzy system and fuzzy wavelet shrinkage | |
Chudasama et al. | Survey on Various Edge Detection Techniques on Noisy Images | |
Wang et al. | Image edge detection algorithm based onwavelet fractional differential theory | |
Godzwon et al. | Biometrics image denoising algorithm based on contourlet transform | |
Sargolzaei et al. | Impulse image noise reduction using fuzzy-cellular automata method | |
McLaughlin et al. | Modified deconvolution using wavelet image fusion | |
Nair et al. | An efficient directional weighted median switching filter for impulse noise removal in medical images | |
Dehuri et al. | A comparative analysis of filtering techniques on application in image denoising | |
Saleh et al. | Automated fabric defect detection using à trous wavelet transform and bollinger band (BB) | |
Kundu | Image denoising using patch based processing with fuzzy Gaussian membership function | |
Ma et al. | An overview of digital image analog noise removal based on traditional filtering | |
Saraf | A new reweight scheme for bilateral and non-local means approach for image denoising | |
Gao et al. | A new image denoising method based on wavelet multi-scale registration fusion | |
Kalai et al. | Sobel-Freichen Hybrid Filters to Improve Edge Detection Performance |